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Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
In terms of operations, it means enabling data usability along with efficiency and availability. They have to innovate which means driving the business towards digital transformation innovation, cost reduction, and revenue generation. Their role is also to provide supporting analytics with reports on products, customers, operations, and markets.
Chief analytics officer (CAO) is a job title for the senior manager responsible for the analysis of data within an organization, such as a listed company or an educational institution. The CAO often reports to the chief executive officer .
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.
Research involves the collection and analysis of information and data with the intention of founding new knowledge and/or deciphering a new understanding of existing data. [42] Research ability is an analytical skill as it allows individuals to comprehend social implications. [ 40 ]
Therefore, modern organizations are using big data analytics to identify 5 to 10 new data sources that can help them collect and analyze data for improved decision-making. Jonsen (2013) explains that organizations using average analytics technologies are 20% more likely to gain higher returns compared to their competitors who have not ...
Dark data; Data access; Data analysis for fraud detection; Data exploration; Data farming; Data fusion; Data profiling; Data science; Data version control; Data-driven model; Data-informed decision-making; DataOps; Degree-Rips bifiltration; Directional component analysis; Directional-change intrinsic time; DOACROSS parallelism; Document ...
A cloud-based architecture for enabling big data analytics. Data flows from various sources, such as personal computers, laptops, and smart phones, through cloud services for processing and analysis, finally leading to various big data applications. Cloud computing can offer access to large amounts of computational power and storage. [30]
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